Knowledge discovery by an intelligent approach using complex fuzzy sets

Chunshien Li, Feng Tse Chan

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

14 Scopus citations


In the age of rapidly increasing volumes of data, human experts have come to the urgent need to extract useful information from the huge amount of data. Knowldege discovery in databases has obtained much attention for researches and applications in business and in science. In this paper, we present a neuro-fuzzy approach using complex fuzzy sets (CFSs) for the problem of knowledge discovery. A CFS is an advanced fuzzy set, whose membership is complex-valued and characterized by an amplitude function and a phase function. The application of CFSs to the proposed complex neuro-fuzzy system (CNFS) can increase the functional mapping ability to find missing data for knowledge discovery. Moreover, we devise a hybrid learning algorithm to evolve the CNFS for modeling accuracy, combining the artificial bee colony algorithm and the recursive least squares estimator method. The proposed approach to knowledge discovery is tested through experimentation, whose results are compared with those by other approaches. The experimental results indicate that the proposed approach outperforms the compared approaches.

Original languageEnglish
Title of host publicationIntelligent Information and Database Systems - 4th Asian Conference, ACIIDS 2012, Proceedings
Number of pages10
EditionPART 1
StatePublished - 2012
Event4th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2012 - Kaohsiung, Taiwan
Duration: 19 Mar 201221 Mar 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume7196 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference4th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2012


  • artificial bee colony (ABC)
  • complex fuzzy set (CFS)
  • complex neuro-fuzzy system (CNFS)
  • knowledge discovery
  • recursive least squares estimator (RLSE)


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